54 datasets found
  1. T

    United States Inflation Rate

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 11, 2025
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    TRADING ECONOMICS (2025). United States Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/inflation-cpi
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Jun 11, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1914 - May 31, 2025
    Area covered
    United States
    Description

    Inflation Rate in the United States increased to 2.40 percent in May from 2.30 percent in April of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  2. World Happiness Index and Inflation Dataset

    • kaggle.com
    Updated Mar 26, 2025
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    Agra Fintech (2025). World Happiness Index and Inflation Dataset [Dataset]. http://doi.org/10.34740/kaggle/dsv/11174951
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 26, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Agra Fintech
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    Context

    Happiness and well-being are essential indicators of societal progress, often influenced by economic conditions such as GDP and inflation. This dataset combines data from the World Happiness Index (WHI) and inflation metrics to explore the relationship between economic stability and happiness levels across 148 countries from 2015 to 2023. By analyzing key economic indicators alongside social well-being factors, this dataset provides insights into global prosperity trends.

    Content

    This dataset is provided in CSV format and includes 16 columns, covering both happiness-related features and economic indicators such as GDP per capita, inflation rates, and corruption perception. The main columns include:

    Happiness Score & Rank (World Happiness Index ranking per country) Economic Indicators (GDP per capita, inflation metrics) Social Factors (Freedom, Social Support, Generosity) Geographical Information (Country & Continent)

    Acknowledgements

    The dataset is created using publicly available data from World Happiness Report, Gallup World Poll, and the World Bank. It has been structured for research, machine learning, and policy analysis purposes.

    Inspiration

    How do economic factors like inflation, GDP, and corruption affect happiness? Can we predict a country's happiness score based on economic conditions? This dataset allows you to analyze these relationships and build models to predict well-being trends worldwide.

  3. T

    United States Core Inflation Rate

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Apr 10, 2025
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    TRADING ECONOMICS (2025). United States Core Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/core-inflation-rate
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Apr 10, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 28, 1957 - May 31, 2025
    Area covered
    United States
    Description

    Core consumer prices in the United States increased 2.80 percent in May of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  4. Global Inflation rate (1960-present)

    • kaggle.com
    Updated Feb 4, 2025
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    Frederick Salazar Sanchez (2025). Global Inflation rate (1960-present) [Dataset]. https://www.kaggle.com/datasets/fredericksalazar/global-inflation-rate-1960-present/data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 4, 2025
    Dataset provided by
    Kaggle
    Authors
    Frederick Salazar Sanchez
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    Please, if you use this dataset or do you like my work please UPVOTE 👁️

    This dataset provides a comprehensive historical record of inflation rates worldwide, covering the period from 1960 to the present. It includes inflation data at the national level for multiple countries and territories, making it a valuable resource for economic analysis, financial forecasting, and macroeconomic research.

    Data Source: https://datos.bancomundial.org/indicador/FP.CPI.TOTL.ZG?end=2023&start=1960&view=chart

    Key Features:

    ✅ Global Coverage – Inflation rates for countries across all continents.

    ✅ Long-Term Data – Over 60 years of historical records, ideal for trend analysis.

    ✅ Regional Classification – Data categorized by region, sub-region, and intermediate region for in-depth geographic analysis.

    ✅ Standardized Indicators – Based on CPI (Consumer Price Index) inflation rates from reputable sources.

    Potential Use Cases:

    📊 Economic Research – Analyze inflation trends and economic cycles.

    📈 Financial Forecasting – Predict future inflation and its impact on global markets.

    🌍 Policy & Development Studies – Examine regional disparities and economic policies.

    📚 Machine Learning Applications – Train predictive models using historical inflation trends.

    This dataset is an essential tool for economists, data scientists, and financial analysts looking to explore global inflation patterns and their implications on economic stability.

  5. T

    Russia Inflation Rate

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 11, 2025
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    TRADING ECONOMICS (2025). Russia Inflation Rate [Dataset]. https://tradingeconomics.com/russia/inflation-cpi
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Jun 11, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1991 - May 31, 2025
    Area covered
    Russia
    Description

    Inflation Rate in Russia decreased to 9.90 percent in May from 10.20 percent in April of 2025. This dataset provides - Russia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  6. w

    Dataset of books about Unemployment-Effect of inflation on-Econometric...

    • workwithdata.com
    Updated Apr 17, 2025
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    Work With Data (2025). Dataset of books about Unemployment-Effect of inflation on-Econometric models [Dataset]. https://www.workwithdata.com/datasets/books?f=1&fcol0=j0-book_subject&fop0=%3D&fval0=Unemployment-Effect+of+inflation+on-Econometric+models&j=1&j0=book_subjects
    Explore at:
    Dataset updated
    Apr 17, 2025
    Dataset authored and provided by
    Work With Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset is about books. It has 3 rows and is filtered where the book subjects is Unemployment-Effect of inflation on-Econometric models. It features 9 columns including author, publication date, language, and book publisher.

  7. Impact of inflation on consumer spending worldwide 2023

    • statista.com
    Updated May 22, 2025
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    Statista (2025). Impact of inflation on consumer spending worldwide 2023 [Dataset]. https://www.statista.com/statistics/1440244/impact-of-inflation-on-spending-global/
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    Dataset updated
    May 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Worldwide
    Description

    In case prices for goods and services go up significantly in 2023, over 20 percent of consumers around the world said they would shop less in general and cut down on spending as a response. A fifth of survey respondents said they would look for and purchase cheaper and better value products. Less than five percent of those surveyed worldwide believed inflation would be unlikely to impact their habits. What does inflation look like? The world entered a new inflation crisis in 2021, driven by a confluence of factors including the COVID-19 pandemic which restricted global supply chains, and the Russian-Ukraine war which exacerbated food and energy shortages. In 2022, global inflation hit 8.71 percent, the highest annual increase in decades. The rate of inflation is estimated to remain high in the near future, at around 6.9 percent in 2023 and 5.8 percent in 2024. Inflation dominated the list of most important problems facing the world according to a survey conducted in October 2023 – leading ahead of poverty and social inequality, crime and violence, and unemployment. In a global consumer trends survey, the majority of respondents said that inflation impacted them completely or a lot – for instance, seven in 10 respondents in the United States admitted they had been seriously impacted. Inflation’s impact on the holidays The end-of-year holiday season is typically regarded as a period of increased retail spending, driven by a series of major shopping events such as Black Friday and Cyber Monday, as well as the public holidays Thanksgiving and Christmas. However, inflation has put a damper on the holiday cheer, with consumers expressing their intentions to cut back spending amid the cost-of-living crisis. In 2022, a significant share of consumers in Europe said they planned to cut at least some related expenses. In fact, 40 percent of respondents in the United Kingdom planned to cut all expenses related to Black Friday and Christmas.

  8. J

    The effects of real and nominal uncertainty on inflation and output growth:...

    • journaldata.zbw.eu
    • jda-test.zbw.eu
    .data, txt
    Updated Dec 8, 2022
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    Kevin B. Grier; Mark J. Perry; Kevin B. Grier; Mark J. Perry (2022). The effects of real and nominal uncertainty on inflation and output growth: some garch-m evidence (replication data) [Dataset]. http://doi.org/10.15456/jae.2022314.0707180839
    Explore at:
    .data(26814), txt(835)Available download formats
    Dataset updated
    Dec 8, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    Kevin B. Grier; Mark J. Perry; Kevin B. Grier; Mark J. Perry
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In this paper we use GARCH-M methods to test four hypotheses about the effects of real and nominal uncertainty on average inflation and output growth in the United States from 1948 to 1996. We find no evidence that higher inflation uncertainty or higher output growth uncertainty raises the average inflation rate. We also find no support for the idea that more risky output growth is associated with a higher average real growth rate. Our key result is that in a variety of models and sample periods, inflation uncertainty significantly lowers real output growth.

  9. T

    India Inflation Rate

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +14more
    csv, excel, json, xml
    Updated Jun 12, 2025
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    TRADING ECONOMICS (2025). India Inflation Rate [Dataset]. https://tradingeconomics.com/india/inflation-cpi
    Explore at:
    csv, xml, excel, jsonAvailable download formats
    Dataset updated
    Jun 12, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 2012 - May 31, 2025
    Area covered
    India
    Description

    Inflation Rate in India decreased to 2.82 percent in May from 3.16 percent in April of 2025. This dataset provides - India Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  10. N

    Median Household Income Variation by Family Size in Truth Or Consequences,...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
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    Neilsberg Research (2024). Median Household Income Variation by Family Size in Truth Or Consequences, NM: Comparative analysis across 7 household sizes [Dataset]. https://www.neilsberg.com/research/datasets/1b85e8de-73fd-11ee-949f-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Truth or Consequences, New Mexico
    Variables measured
    Household size, Median Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It delineates income distributions across 7 household sizes (mentioned above) following an initial analysis and categorization. Using this dataset, you can find out how household income varies with the size of the family unit. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median household incomes for various household sizes in Truth Or Consequences, NM, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

    Key observations

    • Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Truth Or Consequences did not include 5, 6, or 7-person households. Across the different household sizes in Truth Or Consequences the mean income is $56,928, and the standard deviation is $38,611. The coefficient of variation (CV) is 67.82%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
    • In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $20,161. It then further increased to $110,968 for 4-person households, the largest household size for which the bureau reported a median household income.

    https://i.neilsberg.com/ch/truth-or-consequences-nm-median-household-income-by-household-size.jpeg" alt="Truth Or Consequences, NM median household income, by household size (in 2022 inflation-adjusted dollars)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Household Sizes:

    • 1-person households
    • 2-person households
    • 3-person households
    • 4-person households
    • 5-person households
    • 6-person households
    • 7-or-more-person households

    Variables / Data Columns

    • Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Truth Or Consequences median household income. You can refer the same here

  11. J

    Output and inflation in the long run (replication data)

    • journaldata.zbw.eu
    • jda-test.zbw.eu
    txt, zip
    Updated Dec 8, 2022
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    Neil R. Ericsson; John S. Irons; Ralph W. Tryon; Neil R. Ericsson; John S. Irons; Ralph W. Tryon (2022). Output and inflation in the long run (replication data) [Dataset]. http://doi.org/10.15456/jae.2022314.0708044477
    Explore at:
    txt(14551), zip(2235580)Available download formats
    Dataset updated
    Dec 8, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    Neil R. Ericsson; John S. Irons; Ralph W. Tryon; Neil R. Ericsson; John S. Irons; Ralph W. Tryon
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Cross-country regressions explaining output growth often obtain a negative effect from inflation. However, that result is not robust, due to the selection of countries in sample, temporal aggregation, and omission of consequential variables in levels. This paper demonstrates some implications of these mis-specifications, both analytically and empirically. In particular, for most G-7 countries, annual time series of inflation and the log-level of output are cointegrated, thus rejecting the existence of a long-run relation between output growth and inflation. Typically, output and inflation are positively related in these cointegrating relationships: a price markup model helps to interpret this surprising feature.

  12. H

    Central Bank Independence in the World: A New Data Set

    • dataverse.harvard.edu
    Updated Oct 4, 2016
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    Ana Garriga (2016). Central Bank Independence in the World: A New Data Set [Dataset]. http://doi.org/10.7910/DVN/I2BUGZ
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 4, 2016
    Dataset provided by
    Harvard Dataverse
    Authors
    Ana Garriga
    Description

    This article introduces the most comprehensive dataset on de jure central bank independence (CBI), including yearly data from 182 countries between 1970 and 2012. The dataset identifies statutory reforms affecting CBI, their direction, and the attributes necessary to build the Cukierman, Webb and Neyapty index. Previous datasets focused on developed countries, and included non-representative samples of developing countries. This dataset’s substantially broader coverage has important implications. First, it challenges the conventional wisdom about central bank reforms in the world, revealing CBI increases and restrictions in decades and regions previously considered barely affected by reforms. Second, the inclusion of almost 100 countries usually overlooked in previous studies suggests that the sample selection may have substantially affected results. Simple analyses show that the associations between CBI and inflation, unemployment or growth are very sensitive to sample selection. Finally, the dataset identifies numerous CBI decreases (restrictions), whereas previous datasets mostly look at CBI increases. These data’s coverage not only allows researchers to test competing explanations of the determinants and effects of CBI in a global sample, but it also provides a useful instrument for cross-national studies in diverse fields, such as liberalization, diffusion, political institutions, democratization, or responses to financial crises.

  13. T

    Vietnam Inflation Rate

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 6, 2025
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    TRADING ECONOMICS (2025). Vietnam Inflation Rate [Dataset]. https://tradingeconomics.com/vietnam/inflation-cpi
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    Jun 6, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1996 - May 31, 2025
    Area covered
    Vietnam
    Description

    Inflation Rate in Vietnam increased to 3.24 percent in May from 3.12 percent in April of 2025. This dataset provides the latest reported value for - Vietnam Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  14. J

    Oil prices, gasoline prices, and inflation expectations (replication data)

    • journaldata.zbw.eu
    • jda-test.zbw.eu
    txt, zip
    Updated Dec 7, 2022
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    Lutz Kilian; Xiaoqing Zhou; Lutz Kilian; Xiaoqing Zhou (2022). Oil prices, gasoline prices, and inflation expectations (replication data) [Dataset]. http://doi.org/10.15456/jae.2022327.072416
    Explore at:
    zip(118513277), txt(1970)Available download formats
    Dataset updated
    Dec 7, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    Lutz Kilian; Xiaoqing Zhou; Lutz Kilian; Xiaoqing Zhou
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    It has long been suspected, given the salience of gasoline prices, that fluctuations in gasoline prices shift households' 1-year inflation expectations. Assessing this view empirically requires the use of dynamic structural models to quantify the cumulative effect of gasoline price shocks on household inflation expectations at each point in time. We find that, on average, gasoline price shocks account for 42% of the variation in these expectations. The cumulative increase in household inflation expectations from early 2009 to early 2013, in particular, is almost entirely explained by unexpectedly rising gasoline prices. However, there is no support for the view that the improved fit of the Phillips curve augmented by household inflation expectations during 2009 2013 is mainly explained by rising gasoline prices.

  15. J

    Replicating the Results in ‘A New Model of Trend Inflation’ Using Particle...

    • journaldata.zbw.eu
    • jda-test.zbw.eu
    csv, pdf, txt
    Updated Dec 7, 2022
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    Nima Nonejad; Nima Nonejad (2022). Replicating the Results in ‘A New Model of Trend Inflation’ Using Particle Markov Chain Monte Carlo (replication data) [Dataset]. http://doi.org/10.15456/jae.2022326.0700407740
    Explore at:
    txt(871), csv(3867), pdf(617550)Available download formats
    Dataset updated
    Dec 7, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    Nima Nonejad; Nima Nonejad
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    An article by Chan et al. (2013) published in the Journal of Business and Economic Statistics introduces a new model for trend inflation. They allow the trend inflation to evolve according to a bounded random walk. In order to draw the latent states from their respective conditional posteriors, they use accept-reject Metropolis-Hastings procedures. We reproduce their results using particle Markov chain Monte Carlo (PMCMC), which approaches drawing the latent states from a different technical point of view by relying on combining Markov chain Monte Carlo and sequential Monte Carlo methods. To conclude: we are able to reproduce the results of Chan et al. (2013).

  16. N

    Truth Or Consequences, NM Median Household Income Trends (2010-2023, in 2023...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
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    Neilsberg Research (2025). Truth Or Consequences, NM Median Household Income Trends (2010-2023, in 2023 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/research/datasets/1714855e-f81d-11ef-a994-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Truth or Consequences, New Mexico
    Variables measured
    Median Household Income, Median Household Income Year on Year Change, Median Household Income Year on Year Percent Change
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It presents the median household income from the years 2010 to 2023 following an initial analysis and categorization of the census data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset illustrates the median household income in Truth Or Consequences, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

    Key observations:

    From 2010 to 2023, the median household income for Truth Or Consequences decreased by $1,573 (5.12%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

    Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 5 years and declined for 8 years.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

    Years for which data is available:

    • 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

    Variables / Data Columns

    • Year: This column presents the data year from 2010 to 2023
    • Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
    • YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
    • YOY Change(%): Percent change in median household income between current and the previous year

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Truth Or Consequences median household income. You can refer the same here

  17. m

    Inflation Expectations Affecting the Personal Finances of Undergraduate...

    • data.mendeley.com
    Updated Sep 15, 2022
    + more versions
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    Deborah George (2022). Inflation Expectations Affecting the Personal Finances of Undergraduate Students [Dataset]. http://doi.org/10.17632/zcxdsw95bm.2
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    Dataset updated
    Sep 15, 2022
    Authors
    Deborah George
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This data-set cited sources that helped assess the interrelationship between savings, spending, and inflation expectations among undergraduate students. It was directed towards discovering the difficulties students may face with their finances because of inflation. A web-based survey was administered to 315 undergraduate students in Nigeria. Data obtained was analyzed using descriptive statistics such as percentage and frequency. The results revealed inflation expectations had a significant negative impact on the spending habits of students. The results further revealed that individual savings attitudes were reduced with an increase in inflation, but overall savings did not.

  18. A

    ‘🚊 Consumer Price Index’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Aug 28, 2013
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2013). ‘🚊 Consumer Price Index’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-consumer-price-index-ba9d/latest
    Explore at:
    Dataset updated
    Aug 28, 2013
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘🚊 Consumer Price Index’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/consumer-price-indexe on 13 February 2022.

    --- Dataset description provided by original source is as follows ---

    About this dataset

    9The Consumer Price Index for All Urban Consumers: All Items (CPIAUCSL) is a measure of the average monthly change in the price for goods and services paid by urban consumers between any two time periods.(1) It can also represent the buying habits of urban consumers. This particular index includes roughly 88 percent of the total population, accounting for wage earners, clerical workers, technical workers, self-employed, short-term workers, unemployed, retirees, and those not in the labor force.(1)

    The CPIs are based on prices for food, clothing, shelter, and fuels; transportation fares; service fees (e.g., water and sewer service); and sales taxes. Prices are collected monthly from about 4,000 housing units and approximately 26,000 retail establishments across 87 urban areas.(1) To calculate the index, price changes are averaged with weights representing their importance in the spending of the particular group. The index measures price changes (as a percent change) from a predetermined reference date.(1) In addition to the original unadjusted index distributed, the Bureau of Labor Statistics also releases a seasonally adjusted index. The unadjusted series reflects all factors that may influence a change in prices. However, it can be very useful to look at the seasonally adjusted CPI, which removes the effects of seasonal changes, such as weather, school year, production cycles, and holidays.(1)

    The CPI can be used to recognize periods of inflation and deflation. Significant increases in the CPI within a short time frame might indicate a period of inflation, and significant decreases in CPI within a short time frame might indicate a period of deflation. However, because the CPI includes volatile food and oil prices, it might not be a reliable measure of inflationary and deflationary periods. For a more accurate detection, the core CPI (Consumer Price Index for All Urban Consumers: All Items Less Food & Energy [CPILFESL]) is often used. When using the CPI, please note that it is not applicable to all consumers and should not be used to determine relative living costs.(1) Additionally, the CPI is a statistical measure vulnerable to sampling error since it is based on a sample of prices and not the complete average.(1)

    Attribution: US. Bureau of Labor Statistics from The Federal Reserve Bank of St. Louis

    For more information on the consumer price indexes, see:

    This dataset was created by Finance and contains around 900 samples along with Consumer Price Index For All Urban Consumers: All Items, Title:, technical information and other features such as: - Consumer Price Index For All Urban Consumers: All Items - Title: - and more.

    How to use this dataset

    • Analyze Consumer Price Index For All Urban Consumers: All Items in relation to Title:
    • Study the influence of Consumer Price Index For All Urban Consumers: All Items on Title:
    • More datasets

    Acknowledgements

    If you use this dataset in your research, please credit Finance

    Start A New Notebook!

    --- Original source retains full ownership of the source dataset ---

  19. T

    United States Food Inflation

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Food Inflation [Dataset]. https://tradingeconomics.com/united-states/food-inflation
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    csv, excel, json, xmlAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1914 - May 31, 2025
    Area covered
    United States
    Description

    Cost of food in the United States increased 2.90 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  20. N

    Truth Or Consequences, NM Median Income by Age Groups Dataset: A...

    • neilsberg.com
    csv, json
    Updated Aug 7, 2024
    + more versions
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    Neilsberg Research (2024). Truth Or Consequences, NM Median Income by Age Groups Dataset: A Comprehensive Breakdown of Truth Or Consequences Annual Median Income Across 4 Key Age Groups // 2024 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a3fb0a8c-54ae-11ef-a42e-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Aug 7, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Truth or Consequences, New Mexico
    Variables measured
    Income for householder under 25 years, Income for householder 65 years and over, Income for householder between 25 and 44 years, Income for householder between 45 and 64 years
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. It delineates income distributions across four age groups (Under 25 years, 25 to 44 years, 45 to 64 years, and 65 years and over) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the distribution of median household income among distinct age brackets of householders in Truth Or Consequences. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Truth Or Consequences. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

    Key observations: Insights from 2022

    In terms of income distribution across age cohorts, in Truth Or Consequences, the median household income stands at $74,421 for householders within the 25 to 44 years age group, followed by $28,310 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $24,772.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Age groups classifications include:

    • Under 25 years
    • 25 to 44 years
    • 45 to 64 years
    • 65 years and over

    Variables / Data Columns

    • Age Of The Head Of Household: This column presents the age of the head of household
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Truth Or Consequences median household income by age. You can refer the same here

Share
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Close
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TRADING ECONOMICS (2025). United States Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/inflation-cpi

United States Inflation Rate

United States Inflation Rate - Historical Dataset (1914-12-31/2025-05-31)

Explore at:
149 scholarly articles cite this dataset (View in Google Scholar)
json, excel, xml, csvAvailable download formats
Dataset updated
Jun 11, 2025
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Dec 31, 1914 - May 31, 2025
Area covered
United States
Description

Inflation Rate in the United States increased to 2.40 percent in May from 2.30 percent in April of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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